{
  "schemaVersion": "spacetime.intelligence-investigation/v1",
  "id": "INT-001-SOURCE-LOSS",
  "revision": "2026-09-25-r1",
  "publicationVisibility": "public",
  "question": "How do we find our way when signals disappear?",
  "status": "Executable synthetic investigation",
  "scope": {
    "classification": "synthetic_illustration",
    "place": null,
    "placeReason": "Local frame, not a geographical position solution",
    "extent": {
      "corridorHalfWidthMeters": 20,
      "lookAheadMeters": 60
    },
    "frame": "local_x_left_y_up_z_forward_m",
    "time": {
      "kind": "scenario_elapsed",
      "unit": "second",
      "first": 0,
      "last": 120
    },
    "operationalApplicability": null,
    "operationalApplicabilityReason": "Sensor coefficients are authored; field performance and integrity are not evaluated"
  },
  "sourceReferences": [
    {
      "id": "FOG-FPV-1.2",
      "kind": "authored_synthetic_model",
      "version": "fog-fpv-1.2",
      "path": "/spacetime-intelligence/v1/source-loss-model.mjs",
      "sha256": "b1ecf9a53d781de1a26125077c13eeac5ae2cb4a374375e950eff84d8784ea69",
      "experiment": "/spacetime/research/hci/fog-of-probability"
    }
  ],
  "historicalReferences": [
    {
      "id": "PVS-WAYFINDING",
      "title": "Polynesian wayfinding",
      "publisher": "Polynesian Voyaging Society",
      "url": "https://hokulea.com/polynesian-wayfinding/",
      "relationship": "Cultural and methodological context; not technical ancestry of the synthetic model"
    },
    {
      "id": "RMG-H4",
      "title": "H4 marine timekeeper",
      "publisher": "Royal Museums Greenwich",
      "url": "https://www.rmg.co.uk/collections/objects/rmgc-object-79142",
      "relationship": "Historical example of a navigation instrument; not product validation"
    },
    {
      "id": "CAM-TR696",
      "title": "An introduction to inertial navigation",
      "publisher": "University of Cambridge Computer Laboratory",
      "url": "https://www.cl.cam.ac.uk/techreports/UCAM-CL-TR-696.html",
      "relationship": "Technical background; not the coefficient source or product benchmark"
    }
  ],
  "findings": [
    {
      "id": "F1",
      "kind": "computed_from_synthetic_inputs",
      "statement": "The authored interval widens through source loss and crosses the illustrative corridor in the fallback condition.",
      "comparison": {
        "baselineSeconds": 0,
        "changedSeconds": 75
      },
      "units": "meters",
      "uncertaintyStatus": "Pointwise 95% lateral coverage under independent zero-mean Gaussian assumptions"
    },
    {
      "id": "F2",
      "kind": "inference",
      "statement": "A navigation interface should expose evidence age and applicability alongside its estimate. This experiment motivates that design question; it does not establish a validated policy."
    }
  ],
  "contradictoryEvidence": {
    "status": "not_evaluated",
    "reason": "No empirical sensor or participant comparison is included; correlated errors, bias and incorrect assumptions can invalidate the illustrated coverage."
  },
  "limitations": [
    "No measured positioning accuracy, integrity protection level or trajectory guarantee.",
    "The source-loss and recovery sequence and all sensor coefficients are authored.",
    "The returned sigmaTerrain field is not used in the lateral-interval calculation.",
    "Historical examples are context, not endorsement or direct technical lineage."
  ],
  "nextQuestions": [
    {
      "question": "How does this boundary change with recorded observations and a stated mission requirement?",
      "action": "/spacetime/research/replay",
      "label": "Open the capture viewer"
    }
  ],
  "authors": [
    {
      "name": "Spacetime",
      "role": "public investigation publisher"
    }
  ],
  "reviewEvents": [],
  "artifacts": [
    {
      "id": "SYNTHETIC-SOURCE-LOSS-121",
      "kind": "computed_fixture",
      "path": "/spacetime-intelligence/v1/source-loss.json",
      "sourceId": "FOG-FPV-1.2",
      "samples": 121
    }
  ],
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      "provenance": "authored_synthetic",
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      "distribution": "independent_zero_mean_gaussian",
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